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Risk Exposure, Liquidity and Bank Performance: New Evidence from the Recent Financial Crisis of 2007–2008

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Creative Business and Social Innovations for a Sustainable Future

Part of the book series: Advances in Science, Technology & Innovation ((ASTI))

Abstract

In this paper, we examine the main determinants of stock return performance of 178 large and medium sized banks across the world, during the recent financial crisis of 2007–2008. We test the validity of various hypotheses advanced in the academic literature to address the question of why some banks performed so poorly during the crisis. Previous empirical analysis reports that the fragility of banks financed with short-term funds raised in capital markets, as well as the insufficient capital are among the factors that can explain the poor bank performance during the crisis. Our analysis brings new evidences in support of these arguments. We find that financial institutions with less deposits and loans, more liquid assets, lower return, lower ex-ante risk, and more funding fragility ahead of the crisis performed more poorly during the crisis. We investigate the impact of regulations on bank performance and find a strong correlation between restrictions on bank activities and bank stock return only in the sample of large banks. However, no systematic evidence exists that such restrictions made banks less risky before the crisis. Our main results hold up in a variety of robustness tests.

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Notes

  1. 1.

    Because no evidence exists that these banks had less risk ex ante, banks with more restrictions on their activities could have had higher returns because they did not have the opportunity to diversify into activities that unexpectedly performed poorly during the crisis.

  2. 2.

    Both [11] and [12] claim that one of the reasons to have such a decrease in bank assets is related to the so-called “asymmetric information” problem as proposed by Akerlof [13].

  3. 3.

    Adrian and Shin [4] test the response of the financial institutions to possible changes in their net worth and find a positive relation between changes in leverage and changes in balance sheet size, rather than the expected negative one. They conclude that financial institutions adjusting their balance sheet actively end up with high leverage position during booms and low during busts. Their conclusion is that the leverage is procyclical.

  4. 4.

    Rogers [20] argues that banks have taken part in the so-called noninterest activities for a considerable time. Nonetheless, these activities are considered as non-traditional operations of banks. The “traditional” model is known as originate-to-hold. In this model, banks use the money they obtained from outside depositors to fund loans and return the money to the owners after the maturity period elapsed.

  5. 5.

    Folkerts-Landau and Lindgren [21] propose that the introduction of insurance in the banking system could reduce the fragility of banks. However, Refs. [22, 23] argue that the excessive reliance on deposit insurance could affect bank stability. In other words, insurance can encourage banks to raise their exposure to liquidity risk.

  6. 6.

    Myers and Majluf [25, Ross 26] were the pioneers of signaling theory. They claim that signals could affect the firm value due to the presence of asymmetric information.

  7. 7.

    Bebchuk and Spamann [1] argue that the weak features of the corporate governance played an utmost role in the performance of banks during the recent financial turmoil. The study also emphasizes that “executive compensation arrangements” could have influenced the immoderate risk taking. This means managers had incentives to take an excessive amount of risk in order to raise their compensation.

  8. 8.

    See Refs. [7, 34, 35] for an additional overview of this issue.

  9. 9.

    Some of the largest banks are subject to data limitation; for example, Deutsche Bank has no complete data available in Bankscope before 2005.

  10. 10.

    Capital measures and other explanatory variables are explained in Appendix.

  11. 11.

    The survey consists of questions sent to regulators and most questions required a yes or no answer. The third survey had more than three hundred questions and had responses from 142 countries.

  12. 12.

    Much attention has been paid to the moral hazard created by deposit insurance, and prior empirical research shows that explicit deposit insurance is associated with less bank stability [22]. Most countries in our sample have explicit deposit insurance system. Our preliminary tests show that this variable is insignificant in all model specifications and it was dropped from the analysis.

  13. 13.

    Beltratti and Stulz[5] construct an index for whether the board was shareholder-friendly in 2006, board. The index is higher for more independent boards and is lower for staggered boards. The study finds that banks with more shareholder-friendly boards performed significantly worse during the crisis than other banks. Because of data limitation we were unable to investigate this relationship.

  14. 14.

    To compute the variables in Tables 1 and 2, we use the following sources of information: Bankscope, Datastream, OSIRIS, OECD statistics, FDIC, Annual reports, The World Bank (WDI) database, National banking statistics, IMF database, Yahoo Finance, and Thomson Reuters.

  15. 15.

    We do not report in Table 4 the estimates of the country fixed effects but they are available upon request. Based on Hausman [46] test we report the models in Tables 4 and 5 as fixed effect specifications.

  16. 16.

    According to many scholars and researchers (see [2, 4,5,6]), non-interest activities and short-term funding were considered as a major cause of the excessive bank risk exposure. It is well known that these activities generate higher returns due to their complexity and diversification.

  17. 17.

    We believe this analysis is particularly important as it may bring additional evidence in support of the hypothesis that there should be a positive relation between restrictions on bank activities and their risk exposure. This is also in line with our hypothesis that tighter regulations helped reduce bank risk during the recent financial crisis.

  18. 18.

    Specifically, we used Arellano Bover-Blundell-Bond Estimation with the following features: (1) One-step estimator with 95% confidence level, (2) one lag for the dependent variable which is significant, and 15 “max lags of the predetermined variables for use as instruments”, (3) for the Standard Error type the GMM (Default Standard Error) is used, and (4) lags for the regulatory and macroeconomic variables due to endogeneity.

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Author information

Authors and Affiliations

  1. American University in the Emirates, International Academic City, Dubai, UAE

    Miroslav Mateev

  2. School of Management, University of Bath, Building 8 West, Quarry Road, Bath, UK

    Petko Bachvarov

Authors
  1. Miroslav Mateev
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  2. Petko Bachvarov
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Correspondence to Miroslav Mateev .

Editor information

Editors and Affiliations

  1. American University in the Emirates, Dubai, United Arab Emirates

    Miroslav Mateev

  2. UCLan Cyprus, Larnaka, Cyprus

    Panikkos Poutziouris

Appendix

Appendix

See Table 10

Table 10 Dependent and explanatory variables
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Mateev, M., Bachvarov, P. (2019). Risk Exposure, Liquidity and Bank Performance: New Evidence from the Recent Financial Crisis of 2007–2008. In: Mateev, M., Poutziouris, P. (eds) Creative Business and Social Innovations for a Sustainable Future. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-030-01662-3_25

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